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Videos

Clase 29 Nov

Clase 30 Nov

",{"_133":134,"_43":44,"_46":-5,"_45":44,"_62":63,"_135":136,"_149":131},"previewContent","

\n BASE 1 to Clustering\n
- \n PASO 1 Archvio Base\n
- \n PASO 2 Código\n
\n
\n BASE 2 to Clustering\n
- \n PASO 1 Archvios Base\n
- \n PASO 2 Datos Carga\n
\n
\n BASE 3 to Clustering\n
- \n PASO 1\n
- \n Paso 2\n
\n
\n Videos\n
- \n Clase 29 Nov\n
- \n Clase 30 Nov\n
\n

BASE 1 to Clustering

PASO 1 Archvio Base

Descarga el archivo de abajo para empezar tu proyecto :

Archivo de R con base 1

PASO 2 Código

Deberas correr los chuncks de abajo para empezar el proyecto :

set.seed(351)\ndf <- USArrests\nmurder3 <- df[sample(nrow(df), 45),]\nrm(df)\n

\n\n

This data set contains statistics, in arrests per 100000 residents\nfor assault, murder, and rape in each of the 50 US states in 1973

# Also given is the percent of the population living in urban areas.\n\nA data frame with 45 observations on 4 variables.\n[,1]    Murder  numeric Murder arrests (per 100,000)\n[,4]    Rape    numeric Rape arrests (per 100,000)\n[,3]    UrbanPop    numeric Percent urban population\n[,4]    Rape    numeric Rape arrests (per 100,000)\n

\n\n

Escalamos la base y usaremos murder4

murder4 <- as.data.frame(scale(murder3))\n

\n\n\n

BASE 2 to Clustering

PASO 1 Archvios Base

Descarga los archivos de abajo para empezar tu proyecto :

Baja ambos archivos para él proyecto

base 2 R

Datos Base 2 poner en la misma carpeta

PASO 2 Datos Carga

CORRE este chunk para Cargar los Datos

Datos de diferentes auto del modelo Audi, se busca ver si es posible agrupar los modelos de autos

fuel2 <- read.csv(\"combustible.csv\")\nfuel2$Carrocería <- NULL\nfuel2$Caja_cambios <- NULL\nfuel2$Marchas <- NULL\nfuel2$Combustible <- NULL\nboxplot(fuel2,main=\"las variables NO ESTAN en el mismo RANGO !! \")\n

\n\n

NOMBRES DE LAS VARIABLES DEL DATASET

names(fuel2)   \n

\n\n

nombres

## [1] \"Velocidad_max\"     \"Diámetro_cilindro\" \"Recorrido_pistón\" \n## [4] \"Potencia_motor\"    \"Cilindrada\"\n

\n\n

Escalamos la base y usaremos fuel3

fuel3 <- as.data.frame(scale(fuel2))\nboxplot(fuel3,main=\"Ahora todas las variables están en el mismo rango !! \")\n

\n\n

\n\n

BASE 3 to Clustering

PASO 1

CORRE este chunk para Cargar los Datos

url = \"http://www.biz.uiowa.edu/faculty/jledolter/DataMining/protein.csv\"\nfood <- read.csv(url)\n\nrownames(food) <- food$Country\nfood$Country <- NULL\nnames(food)\n

\n\n

Nombres de las variables

## [1] \"RedMeat\"   \"WhiteMeat\" \"Eggs\"      \"Milk\"      \"Fish\"      \"Cereals\"  \n## [7] \"Starch\"    \"Nuts\"      \"Fr.Veg\"\n

\n\n

Paso 2

nivel de las variables

boxplot(food)\n

\n\n

escalamiento de las variables

food2 <- as.data.frame(scale(food))\nboxplot(food2)\n

\n\n

\n\n

Videos

Clase 29 Nov

Clase 30 Nov

\n\n

\n\n","tocStructure",[137,138,139,140,141,142,143,144,145,146,147,148],{"_72":73,"_43":74,"_67":-5,"_75":76,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":81,"_43":82,"_67":-5,"_75":83,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":81,"_43":88,"_67":-5,"_75":89,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":73,"_43":91,"_67":-5,"_75":92,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":81,"_43":95,"_67":-5,"_75":96,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":81,"_43":98,"_67":-5,"_75":99,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":73,"_43":101,"_67":-5,"_75":102,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":81,"_43":105,"_67":-5,"_75":106,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":81,"_43":108,"_67":-5,"_75":109,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":73,"_43":111,"_67":-5,"_75":112,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":81,"_43":115,"_67":-5,"_75":116,"_68":77,"_84":-5,"_85":-5,"_86":-5},{"_72":81,"_43":118,"_67":-5,"_75":119,"_68":77,"_84":-5,"_85":-5,"_86":-5},"publicChapterContent","nextChapter","sections",[147,148],"routes/_store+/_layout","routes/_store+/_readers+/_layout","actionData","errors"]

Videos

Clase 29 Nov

Clase 30 Nov

Table of Contents

BASE 1 to Clustering

PASO 1 Archvio Base

PASO 2 Código

BASE 2 to Clustering

PASO 1 Archvios Base

PASO 2 Datos Carga

BASE 3 to Clustering

PASO 1

Paso 2

Videos

Clase 29 Nov

Clase 30 Nov